Summary

Examining the impact of cognitive load on structure learning

6 agents, 12 issues

Method changes:

  • ?
Demographics (Attention Check)
0
0.25
0.5
0.75
1
Overall
high
(N=51)		 low
(N=37)		 high
(N=46)		 low
(N=54)		 high
(N=41)		 low
(N=56)		 high
(N=53)		 low
(N=43)		 high
(N=45)		 low
(N=38)		 high
(N=236)		 low
(N=228)
age
Mean (SD) 36.7 (12.4) 34.4 (11.7) 36.7 (12.1) 37.4 (10.4) 38.2 (13.2) 35.3 (10.5) 35.3 (10.6) 35.9 (10.8) 39.3 (11.8) 38.9 (15.0) 37.1 (12.0) 36.4 (11.6)
Median [Min, Max] 34.0 [20.0, 72.0] 32.0 [21.0, 66.0] 34.0 [19.0, 65.0] 35.0 [19.0, 64.0] 37.0 [18.0, 69.0] 36.0 [20.0, 63.0] 35.0 [18.0, 55.0] 35.0 [20.0, 61.0] 38.0 [22.0, 73.0] 33.5 [19.0, 68.0] 35.0 [18.0, 73.0] 34.0 [19.0, 68.0]
race
Asian 4 (7.8%) 4 (10.8%) 6 (13.0%) 4 (7.4%) 6 (14.6%) 12 (21.4%) 4 (7.5%) 5 (11.6%) 3 (6.7%) 5 (13.2%) 23 (9.7%) 30 (13.2%)
Black or African-American 10 (19.6%) 5 (13.5%) 8 (17.4%) 4 (7.4%) 7 (17.1%) 3 (5.4%) 11 (20.8%) 6 (14.0%) 3 (6.7%) 4 (10.5%) 39 (16.5%) 22 (9.6%)
Hispanic/Latinx 6 (11.8%) 2 (5.4%) 0 (0%) 6 (11.1%) 2 (4.9%) 5 (8.9%) 4 (7.5%) 5 (11.6%) 3 (6.7%) 1 (2.6%) 15 (6.4%) 19 (8.3%)
White 31 (60.8%) 26 (70.3%) 31 (67.4%) 37 (68.5%) 24 (58.5%) 36 (64.3%) 33 (62.3%) 26 (60.5%) 35 (77.8%) 26 (68.4%) 154 (65.3%) 151 (66.2%)
American Indian or Alaska Native 0 (0%) 0 (0%) 1 (2.2%) 2 (3.7%) 1 (2.4%) 0 (0%) 1 (1.9%) 1 (2.3%) 1 (2.2%) 1 (2.6%) 4 (1.7%) 4 (1.8%)
Other 0 (0%) 0 (0%) 0 (0%) 1 (1.9%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (0.4%)
Native Hawaiian or Other Pacific Islander 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (2.4%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (2.6%) 1 (0.4%) 1 (0.4%)
gender
Another gender not listed here 1 (2.0%) 0 (0%) 0 (0%) 1 (1.9%) 0 (0%) 0 (0%) 1 (1.9%) 0 (0%) 0 (0%) 0 (0%) 2 (0.8%) 1 (0.4%)
Man 25 (49.0%) 15 (40.5%) 25 (54.3%) 25 (46.3%) 14 (34.1%) 23 (41.1%) 28 (52.8%) 17 (39.5%) 22 (48.9%) 19 (50.0%) 114 (48.3%) 99 (43.4%)
Non-binary 1 (2.0%) 2 (5.4%) 1 (2.2%) 0 (0%) 0 (0%) 1 (1.8%) 1 (1.9%) 1 (2.3%) 1 (2.2%) 0 (0%) 4 (1.7%) 4 (1.8%)
Woman 24 (47.1%) 20 (54.1%) 20 (43.5%) 28 (51.9%) 27 (65.9%) 32 (57.1%) 23 (43.4%) 25 (58.1%) 20 (44.4%) 18 (47.4%) 114 (48.3%) 123 (53.9%)
Prefer not to answer 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (4.4%) 1 (2.6%) 2 (0.8%) 1 (0.4%)
matrix_acc
Mean (SD) 0.846 (0.183) 0.936 (0.0865) 0.837 (0.173) 0.965 (0.0615) 0.777 (0.244) 0.931 (0.145) 0.764 (0.248) 0.892 (0.169) 0.736 (0.243) 0.924 (0.107) 0.793 (0.223) 0.931 (0.122)
Median [Min, Max] 0.875 [0.250, 1.00] 1.00 [0.750, 1.00] 0.875 [0.250, 1.00] 1.00 [0.750, 1.00] 0.875 [0, 1.00] 1.00 [0.125, 1.00] 0.875 [0, 1.00] 0.875 [0, 1.00] 0.750 [0, 1.00] 1.00 [0.625, 1.00] 0.875 [0, 1.00] 1.00 [0, 1.00]
as.factor(matrix_n_correct)
0 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (4.9%) 0 (0%) 2 (3.8%) 1 (2.3%) 1 (2.2%) 0 (0%) 5 (2.1%) 1 (0.4%)
1 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (1.8%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (0.4%)
2 2 (3.9%) 0 (0%) 1 (2.2%) 0 (0%) 0 (0%) 0 (0%) 2 (3.8%) 0 (0%) 2 (4.4%) 0 (0%) 7 (3.0%) 0 (0%)
3 0 (0%) 0 (0%) 1 (2.2%) 0 (0%) 2 (4.9%) 0 (0%) 3 (5.7%) 0 (0%) 3 (6.7%) 0 (0%) 9 (3.8%) 0 (0%)
4 2 (3.9%) 0 (0%) 1 (2.2%) 0 (0%) 3 (7.3%) 0 (0%) 1 (1.9%) 0 (0%) 2 (4.4%) 0 (0%) 9 (3.8%) 0 (0%)
5 4 (7.8%) 0 (0%) 4 (8.7%) 0 (0%) 1 (2.4%) 1 (1.8%) 4 (7.5%) 1 (2.3%) 9 (20.0%) 2 (5.3%) 22 (9.3%) 4 (1.8%)
6 7 (13.7%) 4 (10.8%) 9 (19.6%) 1 (1.9%) 8 (19.5%) 6 (10.7%) 13 (24.5%) 5 (11.6%) 9 (20.0%) 3 (7.9%) 46 (19.5%) 19 (8.3%)
7 17 (33.3%) 11 (29.7%) 15 (32.6%) 13 (24.1%) 16 (39.0%) 9 (16.1%) 15 (28.3%) 16 (37.2%) 7 (15.6%) 11 (28.9%) 70 (29.7%) 60 (26.3%)
8 19 (37.3%) 22 (59.5%) 15 (32.6%) 40 (74.1%) 9 (22.0%) 39 (69.6%) 13 (24.5%) 20 (46.5%) 12 (26.7%) 22 (57.9%) 68 (28.8%) 143 (62.7%)
0
0.25
0.5
0.75
1
Overall
high
(N=2)		 low
(N=4)		 high
(N=3)		 low
(N=2)		 high
(N=3)		 low
(N=3)		 high
(N=5)		 low
(N=1)		 high
(N=4)		 low
(N=7)		 high
(N=17)		 low
(N=17)
age
Mean (SD) 37.5 (7.78) 33.8 (3.10) 44.0 (13.5) 31.0 (5.66) 30.7 (2.31) 41.3 (19.1) 39.4 (8.59) 27.0 (NA) 25.5 (5.45) 38.1 (12.3) 35.2 (9.97) 36.2 (11.1)
Median [Min, Max] 37.5 [32.0, 43.0] 33.0 [31.0, 38.0] 45.0 [30.0, 57.0] 31.0 [27.0, 35.0] 32.0 [28.0, 32.0] 34.0 [27.0, 63.0] 40.0 [26.0, 49.0] 27.0 [27.0, 27.0] 26.5 [19.0, 30.0] 34.0 [24.0, 54.0] 32.0 [19.0, 57.0] 34.0 [24.0, 63.0]
race
Black or African-American 1 (50.0%) 0 (0%) 1 (33.3%) 0 (0%) 1 (33.3%) 1 (33.3%) 2 (40.0%) 1 (100%) 0 (0%) 4 (57.1%) 5 (29.4%) 6 (35.3%)
White 1 (50.0%) 3 (75.0%) 1 (33.3%) 2 (100%) 2 (66.7%) 1 (33.3%) 1 (20.0%) 0 (0%) 4 (100%) 3 (42.9%) 9 (52.9%) 9 (52.9%)
Asian 0 (0%) 1 (25.0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (5.9%)
American Indian or Alaska Native 0 (0%) 0 (0%) 1 (33.3%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (5.9%) 0 (0%)
Hispanic/Latinx 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (33.3%) 2 (40.0%) 0 (0%) 0 (0%) 0 (0%) 2 (11.8%) 1 (5.9%)
gender
Woman 2 (100%) 4 (100%) 2 (66.7%) 0 (0%) 1 (33.3%) 1 (33.3%) 2 (40.0%) 0 (0%) 2 (50.0%) 5 (71.4%) 9 (52.9%) 10 (58.8%)
Man 0 (0%) 0 (0%) 1 (33.3%) 2 (100%) 2 (66.7%) 2 (66.7%) 3 (60.0%) 1 (100%) 2 (50.0%) 2 (28.6%) 8 (47.1%) 7 (41.2%)
matrix_acc
Mean (SD) 0.313 (0.265) 0.813 (0.161) 0.917 (0.144) 0.938 (0.0884) 0.750 (0.217) 0.917 (0.144) 0.800 (0.112) 0.750 (NA) 0.781 (0.213) 0.982 (0.0472) 0.750 (0.234) 0.912 (0.123)
Median [Min, Max] 0.313 [0.125, 0.500] 0.813 [0.625, 1.00] 1.00 [0.750, 1.00] 0.938 [0.875, 1.00] 0.625 [0.625, 1.00] 1.00 [0.750, 1.00] 0.875 [0.625, 0.875] 0.750 [0.750, 0.750] 0.813 [0.500, 1.00] 1.00 [0.875, 1.00] 0.750 [0.125, 1.00] 1.00 [0.625, 1.00]
Agent Learning Plots
NonDeviant Analysis
Analysis of Deviance Table (Type II Wald chisquare tests)

Response: corrresp
                                               Chisq Df Pr(>Chisq)    
opinion_round                               252.5145  1     <2e-16 ***
Deviant_threshold                             6.0055  4     0.1987    
matrix_cond                                   0.0297  1     0.8631    
opinion_round:Deviant_threshold               2.9997  4     0.5579    
opinion_round:matrix_cond                     0.1250  1     0.7236    
Deviant_threshold:matrix_cond                 2.8825  4     0.5777    
opinion_round:Deviant_threshold:matrix_cond   3.1339  4     0.5357    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
 1       opinion_round.trend     SE  df asymp.LCL asymp.UCL z.ratio p.value
 overall               0.167 0.0105 Inf     0.146     0.188  15.852  <.0001

Results are averaged over the levels of: Deviant_threshold, matrix_cond 
Confidence level used: 0.95 
$emmeans
 Deviant_threshold emmean     SE  df asymp.LCL asymp.UCL z.ratio p.value
 0                   1.40 0.0941 Inf      1.22      1.59  14.903  <.0001
 0.25                1.25 0.0868 Inf      1.08      1.42  14.404  <.0001
 0.5                 1.18 0.0884 Inf      1.01      1.36  13.382  <.0001
 0.75                1.20 0.0889 Inf      1.03      1.38  13.551  <.0001
 1                   1.13 0.0949 Inf      0.94      1.31  11.865  <.0001

Results are averaged over the levels of: matrix_cond 
Results are given on the logit (not the response) scale. 
Confidence level used: 0.95 

$contrasts
 contrast                                      estimate    SE  df asymp.LCL
 Deviant_threshold0 - Deviant_threshold0.25      0.1527 0.128 Inf   -0.1958
 Deviant_threshold0 - Deviant_threshold0.5       0.2199 0.129 Inf   -0.1317
 Deviant_threshold0 - Deviant_threshold0.75      0.1983 0.129 Inf   -0.1541
 Deviant_threshold0 - Deviant_threshold1         0.2763 0.133 Inf   -0.0877
 Deviant_threshold0.25 - Deviant_threshold0.5    0.0672 0.124 Inf   -0.2702
 Deviant_threshold0.25 - Deviant_threshold0.75   0.0456 0.124 Inf   -0.2927
 Deviant_threshold0.25 - Deviant_threshold1      0.1236 0.128 Inf   -0.2268
 Deviant_threshold0.5 - Deviant_threshold0.75   -0.0216 0.125 Inf   -0.3630
 Deviant_threshold0.5 - Deviant_threshold1       0.0564 0.130 Inf   -0.2970
 Deviant_threshold0.75 - Deviant_threshold1      0.0780 0.130 Inf   -0.2762
 asymp.UCL z.ratio p.value
     0.501   1.195  0.7542
     0.571   1.706  0.4301
     0.551   1.535  0.5397
     0.640   2.070  0.2330
     0.405   0.543  0.9828
     0.384   0.367  0.9961
     0.474   0.962  0.8720
     0.320  -0.173  0.9998
     0.410   0.435  0.9925
     0.432   0.601  0.9750

Results are averaged over the levels of: matrix_cond 
Results are given on the log odds ratio (not the response) scale. 
Confidence level used: 0.95 
Conf-level adjustment: tukey method for comparing a family of 5 estimates 
P value adjustment: tukey method for comparing a family of 5 estimates 
$emmeans
 matrix_cond emmean     SE  df asymp.LCL asymp.UCL z.ratio p.value
 high          1.23 0.0567 Inf      1.12      1.35  21.779  <.0001
 low           1.23 0.0582 Inf      1.12      1.35  21.152  <.0001

Results are averaged over the levels of: Deviant_threshold 
Results are given on the logit (not the response) scale. 
Confidence level used: 0.95 

$contrasts
 contrast   estimate    SE  df asymp.LCL asymp.UCL z.ratio p.value
 high - low  0.00265 0.081 Inf    -0.156     0.161   0.033  0.9739

Results are averaged over the levels of: Deviant_threshold 
Results are given on the log odds ratio (not the response) scale. 
Confidence level used: 0.95
Similarity Plot
Similarity Analysis
Type III Analysis of Variance Table with Satterthwaite's method
                                         Sum Sq Mean Sq NumDF DenDF  F value
targetpair                                  393     393     1   464   1.5225
Deviant_threshold                         67388   67388     1   464 260.8456
matrix_cond                                 228     228     1   464   0.8820
targetpair:Deviant_threshold              49180   49180     1   464 190.3684
targetpair:matrix_cond                       11      11     1   464   0.0433
Deviant_threshold:matrix_cond                 0       0     1   464   0.0001
targetpair:Deviant_threshold:matrix_cond     17      17     1   464   0.0651
                                         Pr(>F)    
targetpair                               0.2179    
Deviant_threshold                        <2e-16 ***
matrix_cond                              0.3482    
targetpair:Deviant_threshold             <2e-16 ***
targetpair:matrix_cond                   0.8353    
Deviant_threshold:matrix_cond            0.9906    
targetpair:Deviant_threshold:matrix_cond 0.7988    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
$emtrends
 targetpair Deviant_threshold.trend   SE  df lower.CL upper.CL t.ratio p.value
 DN                          -54.48 2.83 464    -60.0   -48.92 -19.277  <.0001
 NN                           -6.79 2.28 464    -11.3    -2.32  -2.984  0.0030

Results are averaged over the levels of: matrix_cond 
Degrees-of-freedom method: satterthwaite 
Confidence level used: 0.95 

$contrasts
 contrast estimate   SE  df lower.CL upper.CL t.ratio p.value
 DN - NN     -47.7 3.46 464    -54.5    -40.9 -13.797  <.0001

Results are averaged over the levels of: matrix_cond 
Degrees-of-freedom method: satterthwaite 
Confidence level used: 0.95 
# A tibble: 4 × 14
# Groups:   matrix_cond [2]
  matrix_cond id       term        estimate std.error statistic p.value conf.low
  <chr>       <chr>    <chr>          <dbl>     <dbl>     <dbl>   <dbl>    <dbl>
1 high        below_.5 Deviant_th… -12.8         6.61  -1.93     0.0552    -25.9
2 high        above_.5 Deviant_th…  -2.87        8.03  -0.357    0.721     -18.7
3 low         below_.5 Deviant_th… -15.3         6.81  -2.25     0.0257    -28.8
4 low         above_.5 Deviant_th…   0.0338      6.75   0.00502  0.996     -13.3
# ℹ 6 more variables: conf.high <dbl>, r.squared <dbl>, adj.r.squared <dbl>,
#   df <dbl>, df.residual <int>, nobs <int>
ISM Analysis
    New Agent Prediction Plot
    Prediction Analysis
    # A tibble: 4 × 14
# Groups:   matrix_cond [2]
  matrix_cond id       term        estimate std.error statistic p.value conf.low
  <chr>       <chr>    <chr>          <dbl>     <dbl>     <dbl>   <dbl>    <dbl>
1 high        below_.5 Deviant_th…   -10.6      11.1     -0.947   0.345    -32.6
2 high        above_.5 Deviant_th…    -2.31     10.5     -0.221   0.825    -23.0
3 low         below_.5 Deviant_th…   -12.4      11.1     -1.12    0.263    -34.3
4 low         above_.5 Deviant_th…     5.24      9.70     0.540   0.590    -14.0
# ℹ 6 more variables: conf.high <dbl>, r.squared <dbl>, adj.r.squared <dbl>,
#   df <dbl>, df.residual <int>, nobs <int>
    Analysis of Variance Table

Response: confidence
                      Df Sum Sq Mean Sq F value Pr(>F)
deviance               4   2400  600.08  0.9361 0.4427
matrix_cond            1     12   11.98  0.0187 0.8913
deviance:matrix_cond   4   1385  346.30  0.5402 0.7063
Residuals            454 291031  641.04               
    $emmeans
 deviance emmean   SE  df lower.CL upper.CL t.ratio p.value
 0          56.6 2.73 454     51.2     62.0  20.707  <.0001
 0.25       55.1 2.54 454     50.1     60.1  21.694  <.0001
 0.5        50.6 2.60 454     45.5     55.7  19.436  <.0001
 0.75       52.8 2.60 454     47.7     57.9  20.316  <.0001
 1          51.1 2.79 454     45.7     56.6  18.336  <.0001

Results are averaged over the levels of: matrix_cond 
Confidence level used: 0.95 

$contrasts
 contrast                    estimate   SE  df lower.CL upper.CL t.ratio
 deviance0 - deviance0.25       1.506 3.73 454    -8.71    11.73   0.403
 deviance0 - deviance0.5        6.037 3.77 454    -4.30    16.37   1.600
 deviance0 - deviance0.75       3.825 3.77 454    -6.50    14.15   1.014
 deviance0 - deviance1          5.469 3.91 454    -5.23    16.17   1.400
 deviance0.25 - deviance0.5     4.531 3.64 454    -5.43    14.49   1.246
 deviance0.25 - deviance0.75    2.319 3.63 454    -7.63    12.27   0.638
 deviance0.25 - deviance1       3.963 3.77 454    -6.37    14.29   1.051
 deviance0.5 - deviance0.75    -2.212 3.68 454   -12.28     7.86  -0.602
 deviance0.5 - deviance1       -0.568 3.81 454   -11.01     9.88  -0.149
 deviance0.75 - deviance1       1.644 3.81 454    -8.80    12.08   0.431
 p.value
  0.9944
  0.4984
  0.8489
  0.6277
  0.7242
  0.9687
  0.8315
  0.9748
  0.9999
  0.9928

Results are averaged over the levels of: matrix_cond 
Confidence level used: 0.95 
Conf-level adjustment: tukey method for comparing a family of 5 estimates 
P value adjustment: tukey method for comparing a family of 5 estimates
    Moderator: Last Opinion
    0
    (N=88)    		 0.25
    (N=100)    		 0.5
    (N=97)    		 0.75
    (N=96)    		 1
    (N=83)    		 Overall
    (N=464)
    pred_maj
    Yes 14 (15.9%) 18 (18.0%) 15 (15.5%) 19 (19.8%) 20 (24.1%) 86 (18.5%)
    No 74 (84.1%) 82 (82.0%) 81 (83.5%) 77 (80.2%) 62 (74.7%) 376 (81.0%)
    Missing 0 (0%) 0 (0%) 1 (1.0%) 0 (0%) 1 (1.2%) 2 (0.4%) 
    # A tibble: 4 × 14
# Groups:   pred_maj [2]
  pred_maj id      term  estimate std.error statistic p.value conf.low conf.high
  <lgl>    <chr>   <chr>    <dbl>     <dbl>     <dbl>   <dbl>    <dbl>     <dbl>
1 FALSE    below_… Devi…   -11.8       8.17    -1.45    0.148    -27.9      4.25
2 FALSE    above_… Devi…    -1.35      7.66    -0.177   0.860    -16.4     13.7 
3 TRUE     below_… Devi…   -13.6      20.3     -0.669   0.507    -54.4     27.3 
4 TRUE     above_… Devi…    24.1      17.1      1.41    0.164    -10.2     58.4 
# ℹ 5 more variables: r.squared <dbl>, adj.r.squared <dbl>, df <dbl>,
#   df.residual <int>, nobs <int>
    Analysis of Variance Table

Response: confidence
                   Df Sum Sq Mean Sq F value    Pr(>F)    
deviance            4   2227   556.6  0.9086    0.4587    
pred_maj            1  12304 12303.6 20.0843 9.402e-06 ***
deviance:pred_maj   4   2379   594.8  0.9710    0.4231    
Residuals         452 276895   612.6                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    Moderator: PNS
    0
    (N=88)    		 0.25
    (N=100)    		 0.5
    (N=97)    		 0.75
    (N=96)    		 1
    (N=83)    		 Overall
    (N=464)
    pns_med
    High 40 (45.5%) 39 (39.0%) 36 (37.1%) 43 (44.8%) 34 (41.0%) 192 (41.4%)
    Low 47 (53.4%) 60 (60.0%) 61 (62.9%) 53 (55.2%) 49 (59.0%) 270 (58.2%)
    Missing 1 (1.1%) 1 (1.0%) 0 (0%) 0 (0%) 0 (0%) 2 (0.4%) 
    # A tibble: 4 × 14
# Groups:   pns_med [2]
  pns_med id       term  estimate std.error statistic p.value conf.low conf.high
  <chr>   <chr>    <chr>    <dbl>     <dbl>     <dbl>   <dbl>    <dbl>     <dbl>
1 High    below_.5 Devi…  -10.7       13.1    -0.818    0.415    -36.7     15.2 
2 High    above_.5 Devi…    1.43      11.9     0.121    0.904    -22.1     24.9 
3 Low     below_.5 Devi…  -13.8        9.60   -1.44     0.152    -32.8      5.14
4 Low     above_.5 Devi…    0.669      8.78    0.0761   0.939    -16.7     18.0 
# ℹ 5 more variables: r.squared <dbl>, adj.r.squared <dbl>, df <dbl>,
#   df.residual <int>, nobs <int>
    Analysis of Variance Table

Response: confidence
                  Df Sum Sq Mean Sq F value Pr(>F)
deviance           4   2465  616.17  0.9641 0.4269
pns_med            1    519  519.01  0.8121 0.3680
deviance:pns_med   4     82   20.57  0.0322 0.9980
Residuals        452 288883  639.12
    Order of deviant across rounds
    Opinion Round
    0
    (N=464)    		 1
    (N=464)    		 2
    (N=464)    		 3
    (N=464)    		 4
    (N=464)    		 5
    (N=464)    		 6
    (N=464)    		 7
    (N=464)    		 Overall
    (N=3712)
    trialnum
    0 73 (15.7%) 66 (14.2%) 66 (14.2%) 66 (14.2%) 60 (12.9%) 55 (11.9%) 46 (9.9%) 59 (12.7%) 491 (13.2%)
    1 67 (14.4%) 62 (13.4%) 53 (11.4%) 64 (13.8%) 72 (15.5%) 54 (11.6%) 60 (12.9%) 60 (12.9%) 492 (13.3%)
    2 51 (11.0%) 49 (10.6%) 66 (14.2%) 51 (11.0%) 50 (10.8%) 60 (12.9%) 49 (10.6%) 66 (14.2%) 442 (11.9%)
    3 67 (14.4%) 53 (11.4%) 55 (11.9%) 53 (11.4%) 49 (10.6%) 69 (14.9%) 57 (12.3%) 61 (13.1%) 464 (12.5%)
    4 53 (11.4%) 58 (12.5%) 58 (12.5%) 65 (14.0%) 68 (14.7%) 60 (12.9%) 54 (11.6%) 37 (8.0%) 453 (12.2%)
    5 57 (12.3%) 61 (13.1%) 54 (11.6%) 64 (13.8%) 47 (10.1%) 67 (14.4%) 74 (15.9%) 55 (11.9%) 479 (12.9%)
    6 55 (11.9%) 54 (11.6%) 55 (11.9%) 56 (12.1%) 62 (13.4%) 53 (11.4%) 61 (13.1%) 59 (12.7%) 455 (12.3%)
    7 41 (8.8%) 61 (13.1%) 57 (12.3%) 45 (9.7%) 56 (12.1%) 46 (9.9%) 63 (13.6%) 67 (14.4%) 436 (11.7%)
    Things to note
    • The PNS moderator is a median split
    Unresolved
    • all good